Relevance: While colic, excessive crying in an otherwise well infant, affects approximately 10% of newborns, crying, the most common complaint of parents in the first year of life affects up to 40% of families. The problem is that the current approach to the diagnosis of colic and the outcomes of colic research are based on subjective data or parental perception of excessive crying via a written cry diary. Recent research suggests that parent perception of infant crying might be influenced by personal characteristics of the parent. Research also suggests that infants diagnosed with colic may have additional features such as unique cry characteristics which may contribute to perceptions that the cry is excessive. At present, there is no commonly used objective measure of infant crying. To better understand the differentiation between normal crying and colic, an objective measure of infant crying is needed. Purpose: This project is the second part of a multi-phased project that will develop and test a procedure for the analysis of infant vocalization to differentiate a normal cry and a colic cry. The first phase of the project tested the feasibility of acquiring infantile vocalization in normal infants in the home over a 24-hour period with a small, portable and commercially available digital recording system. In addition we determined that the recording system was acceptable to parents, did not interfere with daily activities of the mother or the infant or with mother-infant interactions. Data obtained from this study will be instrumental in the submission of a larger NIH application that will test our automated methods of analysis of infantile vocalization and differentiate perceived excessive crying from colic. Methods: In the next phase of this research we propose to use sound data collected in the home (20 parent- infant dyads) to evolve and test a model focused on automated analysis of crying as normal or colic. The aim of this pilot study is to validate the accuracy of our computerized method of sound data analysis that will identify characteristics of infant vocalizations that are associated with infant crying and produce an automated cry diary (i.e., a readable data print out of cry characteristics)